Controlling privacy in a face recognition application

ABSTRACT

Embodiments of the present invention may involve a method, system, and computer program product for controlling privacy in a face recognition application. A computer may receive an input including a face recognition query and a digital image of a face. The computer may identify a target user associated with a facial signature in a first database based at least in part on a statistical correlation between a detected facial signature and one or more facial signatures in the first database. The computer may extract a profile of the target user from a second database. The profile of the target user may include one or more privacy preferences. The computer may generate a customized profile of the target user. The customized profile may omit one or more elements of the profile of the target user based on the one or more privacy preferences and/or a current context.

BACKGROUND

The present invention relates generally to the field of computing, andmore particularly to controlling privacy in a face recognitionapplication.

Face recognition technologies may be used on mobile phones and wearabledevices and may invade user privacy. A “sensor” mobile user may be ableto identify a “target” mobile users without his or her consent. Existingmobile device manufacturers may not provide privacy mechanisms foraddressing this problem. Existing cloud-based face recognition servicesand companies may not provide face recognition privacy guarantees to theend users.

SUMMARY

Embodiments of the present invention disclose a method for controllingprivacy in a face recognition application. The method may includereceiving an input including a face recognition query and a digitalimage of a face. The method may include identifying a target userassociated with a facial signature in a first database based at least inpart on a statistical correlation between a detected facial signatureand one or more facial signatures in the first database. The method mayinclude extracting a profile of the target user from a second database.The profile of the target user may include one or more privacypreferences. The method may include generating a customized profile ofthe target user. The customized profile may omit one or more elements ofthe profile of the target user based on the one or more privacypreferences.

Embodiments of the present invention disclose a computer program productfor controlling privacy in a face recognition application. The computerprogram product may include a computer readable storage medium havingprogram instructions embodied therewith. The computer readable storagemedium is not a transitory signal per se. The program instructions maybe executable by a computer to cause the computer to perform a method.The method may include receiving an input including a face recognitionquery and a digital image of a face. The method may include identifyinga target user associated with a facial signature in a first databasebased at least in part on a statistical correlation between a detectedfacial signature and one or more facial signatures in the firstdatabase. The method may include extracting a profile of the target userfrom a second database. The profile of the target user may include oneor more privacy preferences. The method may include generating acustomized profile of the target user. The customized profile may omitone or more elements of the profile of the target user based on the oneor more privacy preferences.

Embodiments of the present invention disclose a system for controllingprivacy in a face recognition application. The system may include one ormore computer processors, one or more computer-readable storage media,and program instructions stored on the computer-readable storage mediafor execution by at least one of the one or more processors. The programinstructions may include instructions to receive, by the computer, aninput including a face recognition query and a digital image of a face.The program instructions may include instructions to identify, by thecomputer, a target user associated with a facial signature in a firstdatabase based at least in part on a statistical correlation between adetected facial signature and one or more facial signatures in the firstdatabase. The program instructions may include instructions to extract,by the computer, a profile of the target user from a second database.The profile may include one or more privacy preferences. The programinstructions may include instructions to generate, by the computer, acustomized profile of the target user, wherein the customized profileomits one or more elements of the profile of the target user based onthe one or more privacy preferences.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The following detailed description, given by way of example and notintended to limit the invention solely thereto, will best be appreciatedin conjunction with the accompanying drawings.

FIG. 1 depicts a privacy control system, in accordance with anembodiment of the present invention.

FIG. 2 depicts face recognition environment, in accordance with anembodiment of the present invention.

FIGS. 3A-3B depict a privacy control environment, in accordance with anembodiment of the present invention.

FIG. 4 is a flowchart depicting steps of a privacy control application,in accordance with an embodiment of the present invention.

FIG. 5 depicts a block diagram of components of the proxy servercomputer executing the privacy control program, in accordance with anembodiment of the present invention.

FIG. 6 depicts a cloud computing environment, in accordance with anembodiment of the present invention.

FIG. 7 depicts abstraction layers of the cloud computing environment, inaccordance with an embodiment of the present invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention. In the drawings, like numbering representslike elements.

DETAILED DESCRIPTION

Embodiments of the present invention may present a method, system, andapparatus for controlling user privacy in a face recognitionapplication. Face recognition technologies may be increasingly used onmobile phones and wearable devices and may enable a user to invadeanother user's privacy. For example, a sensor user may be able toidentify a target user without his or her consent. Existing mobiledevice manufacturers may not provide any privacy mechanisms foraddressing this problem. For example, a company may ban face recognitionfunctions of wearable glasses, but may not guarantee that this will belong-lived commitment, and the ban may be circumvented by softwaredevelopers. Similarly, existing cloud-based face recognition services orcompanies may not provide face recognition privacy guarantees to endusers. Some existing privacy protection methods may address a differentprivacy problem involving face recognition protection from maliciousapplications or untrusted servers that perform a face recognitioncomputation. However, they may not protect against a trusted userperforming a face recognition request. Conventional face recognitionprivacy opt out proposals may involve requiring a target user to wearspecial apparel that may alter an image captured by a camera. However,this technique requires the target user to wear the special apparel inorder to maintain privacy. In addition to the limitations of existingprivacy opt-out approaches, an additional problem may occur if a targetuser wants to reveal information about themselves in certain situations.Providing context-dependent privacy control for target users (as opposedto just opting out) may enable provide a target user with greaterflexibility while protecting the target user's privacy.

Embodiments of the present invention may include a method and system forprivacy control in face recognition applications. Embodiments include aface recognition system, where users (hereinafter “sensor users”) mayuse a camera to discover information about other people (hereinafter“target users”) using a face recognition service deployed in the cloud.The face recognition service may have access to a face database, aprivacy database, and a profile database. The face database may containone or more facial signatures of one or more users. The profile databasemay contain information about the target user, such as, for example, aname, gender, age, and location. The privacy database may containprivacy preferences of target users. Privacy preferences may be providedby a target user or an operator of a face recognition service and storedin the privacy database. A target user's profile information may beextracted from the profile database. A customized profile may begenerated based on the privacy preferences of the target user. Thecustomized profile may be provided to the sensor user. Embodiments ofthe present invention will now be described in detail with reference toFIGS. 1-6.

FIG. 1 is a privacy control system 100, according to an aspect of theinvention. In an exemplary embodiment, the privacy control system 100may include a computing device 130, a sensor device 115, and a device125. The computing device 130 may include, for example, a processor 116,memory 128, and an input/output (I/O) interface 122. A face recognitionapplication 135 may be a program, function, or module of a computerprogram (not shown) executable by the processor 116.

Privacy control system 100 may be implemented using a computing nodesuch as the cloud computing node of FIG. 5. It is not necessary that thecomputing node described in FIG. 5 be a cloud computing node and may be,instead, implemented using a general purpose computer.

Sensor device 115 may be a laptop computer, tablet computer, netbookcomputer, personal computer (PC), desktop computer, smart phone, or anyprogrammable electronic device. Sensor device 115 may include internaland external hardware components. Sensor device 115 may include anycommunication device known in the art, such as, for example, a Bluetoothdevice, WiFi device, near-field communication (NFC) device, radiofrequency device, or any combination thereof. Sensor device 115 mayinclude an image capturing device, such as, for example, a digitalcamera. Sensor device 115 may be operated by one or more users, such as,for example, a sensor user 110.

Device 125 may be a laptop computer, tablet computer, netbook computer,personal computer (PC), desktop computer, smart phone, or anyprogrammable electronic device. Device 125 may include internal andexternal hardware components. Device 125 may include any communicationdevice known in the art, such as, for example, a Bluetooth device, WiFidevice, near-field communication (NFC) device, radio frequency device,or any combination thereof. Sensor device 115 may include an imagecapturing device, such as, for example, a digital camera. Device 125 maybe operated by one or more users, such as, for example, a target user120.

A network (not shown) may connect the sensor device 115 and/or thedevice 115 to the computing device 130. The network may be anycombination of connections and protocols that will supportcommunications between the devices. In an embodiment, the network may bethe Internet, representing a worldwide collection of networks andgateways to support communications between devices connected to theInternet. The network may include, for example, wired, wireless or fiberoptic connections. In other embodiments, the network may be implementedas an intranet, a local area network (LAN), a wide area network (WAN), acellular network, or a combination thereof. Network 110 may includewired connections, wireless connections, fiber optic connections, or acombination thereof.

In an embodiment, there may be at least two types of input actions inthe system, including privacy preferences and face recognition queries.In a first type of action, the system may receive as an input privacypreferences which control whether, when, where, how and what profilesabout the target user will be shared with the sensor users. Privacypreferences may be submitted by either target users or by an operator ofa face recognition service.

A target user may submit one or more privacy preferences to identifywhich profile, if any, may be returned to a sensor user for a givencontext. The submission of privacy preferences to the system may updatethe privacy database. Such updates may be either static or dynamic. Instatic updates, the target user may define in advance a context and acorresponding profile and upload each to the privacy database. In adynamic update, the target user may change context and create a profileand enable sharing of the profile. As the target user changes contexts(e.g. geographic location, time, situation, mood, etc), the contexts andprofile may be stored as an entry in the privacy database. The entry maybe used again when a same context (e.g. geographic location, time,situation, mood, etc) occurs again (e.g., when the target user is sensedby the sensor user at that context).

An operator of a face recognition service may submit one or more privacypreferences to impose contextual restrictions on where a sensor user mayor not to use the face recognition service. For example, the privacypreferences may be set to not allow usage of face recognition atsensitive locations, times, or occasions. The operator of the facerecognition service may set privacy preferences either statically inadvance or dynamically during the system operation.

In one embodiment, the privacy preferences in the database may beimplemented as database records that contain information pertaining to acontext and a profile that should be used in that context. The contextinformation may consist of (but is not limited to) location, time,objective, situation, face context, etc. A face context may include, forexample, a smile, frown, gender, and age. The profile information mayconsist of multiple items each item type being (but is not limited to)text, video, image or audio. The items may belong to one or morecontexts and a set of items synthesizes a profile that corresponds to aspecific context.

In an embodiment, the privacy database may contain contextualrestrictions which allow (or prevent) sensor users to use the facerecognition service. For example, the system may not allow usage of facerecognition at specific locations or at specific times or at specificoccasions. Such restrictions may be determined by the operator of theface recognition service.

In a second type of input, a sensor user may submit a face recognitionquery along with, for example, a current context and an image and/orvideo to the face recognition system, to identify target users in avicinity. More specifically, the following steps are followed:

The sensor user may submit a face recognition query. The facerecognition query may signal an intention of the sensor user torecognize faces in her vicinity. In addition, it may also define contextand/or profile data of interest to the sensor user. For example, thesensor user may be interested in profiles within a certain context (e.g.geographic region) or profile attributes that describe certaininterests.

In an embodiment, the face recognition system may check a privacydatabase for one or more privacy preferences set by an operator. If asensor user submits a face recognition query with contextualrestrictions in conflict with one or more privacy preferences, the facerecognition query may be blocked.

In another embodiment, a sensor user may submit a video stream to a facedetection application. The face detection application may detect one ormore faces in the video stream and output a set of face signaturescorresponding to the one or more faces in the video stream.

The face signatures may be input to a face recognition application. Theface recognition application may match the face signatures with facesignatures stored in the face database. If no match is found, the facerecognition query terminates and no profile info is returned to thesensor user. Otherwise, the system proceeds as follows.

The face recognition application may output matched target useridentities and their current face context. The current face context maycontain features that express the current state of the target userderived from facial characteristics, which may include but not limitedto smile, frown, gender, color, emotional state (e.g. mood), etc. Withan identity and a current face context of each target user, the systemmay extract a profile, as follows:

The system may check with the privacy database if the target user thatmatches the identity wishes to share profile information. If the targetuser's privacy settings are set not to share, the face recognition queryterminates and no profile info is returned to the sensor user. Otherwisethe system may proceed as follows.

The system may determine the current context of the target user (e.g.current location, time, situation, objective, current face context, or acombination thereof). In an embodiment, if the location of the targetuser is not available, the system may use as an approximation thelocation of the sensor user when determining the current context of thetarget user.

The current context may be matched with the closest context of thistarget user stored in the privacy database. If the closest contextmatches the current context within a specified accuracy threshold, thesystem may retrieve a default profile that has been pre-defined by thetarget user. Otherwise, the system may proceeds as follows:

The system may retrieve the profile of the closest context stored in theprivacy database. In an embodiment, the system may augment the closestcontext in the privacy database by adding to it the current face contextthat was output by the face recognition application.

The retrieved profile and its context may be matched to the context andprofile preferences in the face recognition query of the sensor user. Ifthere is no match, the face recognition query may terminate and may notprovide a profile to the sensor user. Otherwise the system may proceedsas follows:

In an embodiment, the target user's profile may be transmitted to thesensor user. One or more elements of the target user's profile may beomitted based on the privacy preferences.

The system may generate a summary of the outcome of the face recognitionquery. This summary may contains the success or failure of the query,the extracted profile F, the current context C and its closest contextin the privacy database, and the identity of the sensor user. In anembodiment, the summary of the outcome of the face recognition query maybe stored in the privacy database for later access by the target user.

In another embodiment, the system may provide a notification to thetarget users. A first type of notification may include providing thetarget user with a summary of the face recognition query if a facerecognition query occurs. A second type of notification the system maycontinuously track the context changes of the target user (e.g. bymatching the contexts with the existing contexts in the database) and,upon each change, notify the target user about the new profile that willbe shared through the face recognition service.

Referring now to FIG. 2, a face recognition environment 200 is shown, inaccordance with an embodiment of the present invention. The facerecognition environment may include the sensor device 115 and the targetuser 120. In an embodiment, the sensor device 115 may be operated by thesensor user 110. The sensor device 115 may capture an image of thetarget user. The captured image may include, for example, an image ofthe face of the target user 120. The captured image may be a digitalimage. In an embodiment, the captured image may be transmitted to thecomputing device 130.

Referring now to FIGS. 3A-3B, examples of a sensor device are shown, inaccordance with an embodiment of the present invention. In anembodiment, the sensor device 115 (e.g. a sensor device 315) may receivea profile and/or a customized profile of the target user.

In an embodiment, the sensor device 315 may receive a profile of thetarget user. The profile may include one or more elements, such as, forexample, an image of the target user, a name of the target user, agender of the target user, an age of the target user, a location of thetarget user, or any combination thereof. For example, the name of thetarget user may be indicated by providing “Name: John Doe”. The sensordevice 315 may receive the profile from a computing device (e.g. thecomputing device 130).

In an embodiment, the sensor device 315 may receive a customized profileof the target user. The customized profile may include one or moreelements, such as, for example, an image of the target user, a name ofthe target user, a gender of the target user, an age of the target user,a location of the target user, or any combination thereof. In anembodiment, one or more elements may of the customized profile may beprovided based on a context (e.g., a location of the target user). Forexample, when a user is at a location, a particular aspect of herprofile may be revealed or an element of her profile may containdifferent information. For example, if a person is at a businessconference, her profile may contain elements that are specific to thatconference. In another example, if a person is at a sporting event, herprofile may contain elements related to her experience with the sport.In an example, a “nickname” field of the person may change depending onthe context (e.g., a location of the target user). In an embodiment, atleast one element of the customized profile may be censored. Forexample, a name of the target user, an age of the target user, and alocation of the target user may be censored. In an embodiment, acensored element may be hidden or an indication may be given that thecensored element is censored. For example, a name may simply not beincluded in the customized profile. In another example, a censored namemay be provided as “Name: Private” if a name element is censored. In anembodiment, uncensored elements may be included in the customizedprofile and censored elements may not be included. For example, if agender is uncensored and a name is censored the customized profile mayinclude “Gender: Male” and “Name: Private”. In an embodiment, all of theelements of the customized profile may be censored. For example, if allthe elements of the customized profile are censored, an error messagemay be provided (e.g. “This Profile is Private”, “No results found”,etc.) or censored elements may be provided in a censored form (e.g.“Name: Private”). The sensor device 315 may receive the profile from acomputing device (e.g. the computing device 130).

FIG. 4 is a flowchart of a method 400 for controlling privacy in a facerecognition application, using the privacy control system 100 of FIG. 1,in accordance with an embodiment of the present invention. Steps ofmethod 400 may be executed using a processor of a computer thatencompasses, or is part of, privacy control system 100, or anothersystem. In an embodiment, a method of 400 may involve receiving an inputincluding a face recognition query and a digital image of a face (step404), detecting a facial signature from the digital image of the face(step 408), calculating a statistical correlation between the detectedfacial signature and one or more facial signatures in a first database(step 412), identifying a target user associated with the facialsignature in the first database based at least in part on the calculatedstatistical correlation (step 416), extracting a profile of the targetuser from a second database (420), determining whether the profile ofthe target user includes one or more privacy preferences (decision 424),generating a customized profile of the target user with the customizedprofile omitting one or more elements of the profile of the target userbased on the one or more privacy preferences (step 428), transmittingthe profile of the target user to a sensor user (step 432), andtransmitting the customized profile of the target user to a sensor user(step 436).

Step 404 may involve receiving an input including a face recognitionquery and a digital image of a face. In an embodiment, the input may bereceived from the sensor user. For example, a sensor user may submit aface recognition query along with, for example, a current context and animage (e.g. a digital photograph, series of digital photographs, and/ordigital video) to the face recognition system, requesting to identify atarget user depicted in the image.

The face recognition query may signal an intention of the sensor user torecognize one or more faces in the image. In addition, the facerecognition query may also define a context and/or profile data ofinterest to the sensor user. For example, the sensor user may beinterested in profiles within a certain context (e.g. geographic region)or profile attributes that describe certain interests. Metadataassociated with the image may indicate a context of the image (e.g. alocation the image was captured). In an embodiment, the metadataassociated with the image may be used in one or more of the followingsteps. For example, the metadata associated with the image may be usedin step 424 to determine whether privacy preferences associated with atriggering event (e.g. a location a digital image is captured) exist.

Step 408 may involve detecting a facial signature from the digital imageof the face. In an embodiment, an image of a face of a target user maybe analyzed a face detection application. The face detection applicationmay detect one or more faces in the video stream and output a set offacial signatures corresponding to the one or more faces in the image.In an embodiment, the face application may generate a facial signatureby sampling various points of the image of the face, aggregating theinformation associated with the sampling, and hash the sampled pointsinto a face attribute value associated with each sampled point.

Step 412 may involve calculating a statistical correlation between thedetected facial signature and one or more facial signatures in a firstdatabase. The facial signatures may be input into the face recognitionapplication. The face recognition application may calculate astatistical correlation between a facial signature from the image andone or more face signatures stored in the face database. For example, acorrelation probability matrix may provide a likelihood of a matchbetween the facial signature from the image and one or more facialsignatures in a face database. In an example, various face attributevalues associated with various sampled points of the face in the imagemay be compared to corresponding face attribute values of one or morefacial signatures in the face database. If no correlation is found, theface recognition query may terminate and no profile may be generated. Ifa correlation between the face signature in the image and one of theface signatures stored in the face database, the correlation may be usedto identify the target user, as described in step 416.

Step 416 may involve identifying a target user associated with thefacial signature in the first database based at least in part on thecalculated statistical correlation. Identifying the target userassociated with the facial signature in the first database may involvedetermining which user associated with a facial signature in the facedatabase has a highest probability of corresponding the face of thecaptured image. In an embodiment, identifying a target user may be basedon the calculated statistical correlation, metadata associated with theimage of the face (e.g. a location the picture is captured), adetermined location of the target user, one or more second facialsignatures generated from the image, or any combination thereof. In apreferred embodiment, identifying the target user may be based at leastin part on the calculated correlation.

Step 420 may involve extracting a profile of the target user from asecond database. In an embodiment, the profile may include one or moreelements (e.g. an image, name, gender, location, etc.). The one or moreelements may be extracted from the second database (e.g. the profiledatabase). The one or more elements of the profile may be included oromitted from a generated profile depending on an existence of one ormore privacy preferences, described below with reference to decision424.

Decision 424 may involve determining whether one or more privacypreferences exist. Determining whether one or more privacy preferencesexist may involve extracting privacy data from the privacy database. Ifthe privacy data indicates a setting for omitting one or more privacyelements, then privacy preferences may exist. Privacy preferences for aprofile of a target user may be set by, for example, an operator of aface recognition service, the target user, and/or another person.

In an embodiment, the privacy database may contain privacy preferenceswhich allow (or prevent) sensor users to use the face recognitionservice. For example, the system may not allow usage of face recognitionat specific locations or at specific times or at specific occasions. Inanother example, the system may not allow a particular sensor user touse the face recognition service to identify a specific target user or agroup of target users (e.g. if the sensor user has violated terms ofservice in the past). Such privacy preferences may be selected by theoperator of the face recognition service, the target user, and/oranother person.

In an embodiment, the privacy database may contain privacy preferenceswhich prevent specific elements of a profile (e.g. an image, name,gender, location, etc.) from being included in a customized profile. Forexample, the target user may select privacy preferences which prevent animage and a name associated with the profile of the target user frombeing included in a customized profile.

In an embodiment, the privacy preferences may instruct omission of oneor more elements of the profile of the target user if a triggering eventoccurs. A triggering event may include, for example, a location of asensor user, a location of the target user, a location the digital imageis captured, a time the digital image is captured, a time the digitalimage is received, a face context from the face of the digital image,and an identity of a sensor user.

In one embodiment, the privacy preferences in the database may beimplemented as database records that contain information pertaining to acontext and a profile that should be used in that context. The contextinformation may consist of (but is not limited to) location, time,objective, situation, face context, etc. The profile information mayconsist of multiple items each item type being (but is not limited to)text, video, image or audio. The items may belong to one or morecontexts and a set of items synthesizes a profile that corresponds to aspecific context.

Step 428 may involve generating a customized profile of the target userwith the customized profile omitting one or more elements of the profileof the target user based on the one or more privacy preferences. In anembodiment, if a face recognition query in conflict with one or moreprivacy preferences is received, the face recognition query may beblocked, a customized profile may be generated, or a combinationthereof. In an embodiment, if a triggering event occurs (e.g., alocation of a sensor user, a location of the target user, a location thedigital image is captured, a time the digital image is captured, a timethe digital image is received, a face context from the face of thedigital image, and an identity of a sensor user), the face recognitionquery may be blocked, a customized profile may be generated, or acombination thereof. For example, a target user may include a sensoruser on a blocked list in the privacy preferences, triggering acustomized profile to be generated for the sensor user. In anotherexample, an operator of a face recognition service may add an adultentertainment location to a blocked list in the privacy preferences,triggering a customized profile to be generated for images captured inthat location.

The customized profile may omit one or more elements of the profileassociated with the target user. For example, the customized profile mayomit all of the elements and include an error message (e.g., “PrivateProfile”, “No match found”, etc.). In another example, the customizedprofile may omit one or more elements and include one or more elements.For example, the customized profile may omit “Name: John Doe” andinclude “Gender: Male”.

In an embodiment, the system may generate a summary of the outcome ofthe face recognition query. This summary may contain a success orfailure of the query, the extracted profile F, the current context C andits closest context in the privacy database, and the identity of thesensor user. In an embodiment, the summary of the outcome of the facerecognition query may be stored in the privacy database for later accessby the target user.

Steps 432 and step 436 may involve transmitting the profile or thecustomized profile, respectively, of the target user to a sensor user.In step 432, the profile including the profile elements may betransmitted to the sensor user. The profile elements transmitted to thesensor user may include, for example, an image of the target user, aname of the target user, a gender of the target user, an age of thetarget user, and a location of the target user. In step 432, thecustomized profile omitting one or more elements of the profile may betransmitted to the sensor user. The customized profile transmitted tothe sensor user may include, for example, a gender of the target userand may omit, for example, a name of the target user.

In an embodiment, the system may provide a notification to a target userif the profile or the customized profile is transmitted to a sensoruser. For example, the system may provide the target user with a summaryof the face recognition query. In an embodiment, the system maycontinuously track context changes of the target user (e.g. by matchingthe contexts with the existing contexts in the database) and, upon eachchange, notify the target user about the new profile that will be sharedthrough the face recognition service. For example, if the target userenters a location on a blocked list, the system may notify the targetuser that one or more elements of the target user's profile may beomitted in a customized profile.

Referring now to FIG. 5, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 5, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 6, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 5 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 7, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 6) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 7 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and controlling privacy in a mobile facerecognition application 96.

In a related embodiment, cloud migration services may be performed aspart of management layer 80.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of thepresent invention. Therefore, the present invention has been disclosedby way of example and not limitation.

What is claimed is:
 1. A computer system for controlling privacy in aface recognition application, comprising: one or more computer deviceseach having one or more processors and one or more tangible storagedevices; and a program embodied on at least one of the one or morestorage devices, the program having a plurality of program instructionsfor execution by the one or more processors, the program instructionscomprising instructions for: capturing, by a sensor device, a digitalimage of a face; receiving, by the sensor device, a face recognitionquery; detecting, by the sensor device, a facial signature from thedigital image of the face; calculating, by the sensor device, astatistical correlation between the detected facial signature and one ormore facial signatures in a first database; identifying, by the sensordevice, a target user associated with the facial signature in the firstdatabase based at least in part on the statistical correlation betweenthe detected facial signature and the one or more facial signatures inthe first database; extracting, by the sensor device, a profile of thetarget user from a second database, wherein the profile comprises one ormore privacy preferences; generating, by the sensor device, a customizedprofile of the target user, wherein the customized profile omits one ormore elements of the profile of the target user based on the one or moreprivacy preferences and further based on the facial expression of thetarget user, wherein a decision to omit the one or more elements fromthe customized profile is made based on detecting the facial expressionof the target user in the digital image; and providing, by the sensordevice, the customized profile of the target user.